Banks should strengthen data management in these areas to create more value for their customers

With the digitalisation of transactions, agreements, and identity, data has become the primary resource for the financial sector. Traditionally, access to that data has been managed through a so-called role-based access control system. For example, if you were a bank advisor, you had the advisor role, which allowed you to view customer data, which meant you could potentially check the finances of your neighbour, ex-spouse, or even royalty. Increased regulatory pressure to prevent this kind of access makes this model increasingly difficult to implement.

As customers, we expect everything to happen digitally, imposing significant requirements on data management—requirements that banks are not yet fully able to meet, despite their good intentions.

Bank data is often not accessible, accurate, or understandable to the right individuals when they need it. Instead of modern platforms, we often encounter outdated solutions designed by engineers for engineers, hindering data access and use in decision-making across the organisation.

Four key challenges

Here are four key areas that banks should strengthen to create more value for their customers:

1. Ensuring data accuracy and precision

One of the biggest challenges for Danish banks is ensuring that data is accurate and precise. Without correct data, banks risk making poor decisions or overlooking potential risks, which can have serious consequences for both operations and reputation. Errors can stem from manual entries, outdated systems, or a lack of integration between various data sources. The solution requires a robust approach to data governance, with clear policies for data integration, validation, and maintenance. AI and machine learning can help detect and correct errors in real time, while regular audits and standardised processes can ensure quality.

2. Breaking down data silos

Accessible data is crucial for bank decision-makers to respond swiftly and effectively to market demands. Many Danish banks face challenges with data silos, where data is scattered across multiple systems and departments without clear interfaces between them. This makes it difficult to utilise data across the business, hampering the bank’s overall management. Data silos can lead to delays in decision-making processes and hinder quick adaptation to market changes. Modern data infrastructures such as data fabric or data mesh can help break down these silos but they are often costly solutions. An alternative is to implement middleware that creates integration between relevant systems and data sources, allowing data to flow freely without replacing the existing infrastructure. Governance tools can also provide a central overview of critical data, improving the use of data in decision-making.

3. New demands for access control

Increased digitalisation, an intensified threat landscape, and growing regulatory requirements make data access management more complex. Traditional role-based access control, where bank advisors have broad access to customer information, is no longer sufficient. To prevent misuse, such as employees viewing data on family members or high-profile individuals, more detailed roles are required, potentially creating an unmanageable number of roles. The solution lies in attribute-based or dynamic access control, where specific attributes determine who can access which data in a given context. For instance, checking if a customer belongs to the branch where the employee works before granting access. This approach provides greater flexibility and security around data access in modern banks.

4. Ensuring data is understandable

Data must be understandable to create real business value. In many cases, data producers and data consumers do not necessarily interpret data in the same way. This can lead to data created for a specific purpose being used for other purposes, resulting in incorrect decisions. A solution is to establish a common data dictionary containing the key business concepts, where data and terms are clearly explained. The dictionary should indicate who owns the data, where it is located, what it can be used for, and how frequently it is updated. This ensures that data is used correctly throughout the organisation and generates the expected value.

By focusing on these four areas, banks can be better equipped to meet future demands and deliver more tailored and effective solutions to their customers.

Read the article in Danish Børsen here.